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Age-related changes in muscle volume and intramuscular fat content in quadriceps femoris and hamstrings
Journal Pre-proof Age-related changes in muscle volume and intramuscular fat content in quadriceps femoris and hamstrings
Maya Hioki, Nana Kanehira, Teruhiko Koike, Akira Saito, Kiyoshi Shimaoka, Hisataka Sakakibara, Yoshiharu Oshida, Hiroshi Akima PII:
S0531-5565(19)30508-X
DOI:
https://doi.org/10.1016/j.exger.2020.110834
Reference:
EXG 110834
To appear in:
Experimental Gerontology
Received date:
24 July 2019
Revised date:
3 January 2020
Accepted date:
6 January 2020
Please cite this article as: M. Hioki, N. Kanehira, T. Koike, et al., Age-related changes in muscle volume and intramuscular fat content in quadriceps femoris and hamstrings, Experimental Gerontology(2018), https://doi.org/10.1016/j.exger.2020.110834
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© 2018 Published by Elsevier.
Journal Pre-proof Age-related changes in muscle volume and intramuscular fat content in quadriceps femoris and hamstrings
Maya Hiokia, Nana Kanehirab, Teruhiko Koikec, Akira Saitod, e, Kiyoshi Shimaokaf, Hisataka Sakakibaraa, Yoshiharu Oshidac, Hiroshi Akimac
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Graduate School of Medicine, Nagoya University, 65 Tsurumai, Showa-ku, Nagoya, Aichi 466-8550,
Japan Department of Health and Nutrition, Tokaigakuen University, 2-901 Nakahira, Tenpaku, Nagoya, Aichi
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Research Center of Health, Physical Fitness & Sports, Nagoya University, 1 Furo, Chikusa-ku, Nagoya,
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468-8514, Japan
Aichi 464-8601, Japan
Graduate School of Arts and Sciences, College of Arts and Sciences, University of Tokyo, Komaba 3-8-1
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Meguro-ku, Tokyo 153-8092, Japan
Japan Society for the Promotion of Science, Kojimachi, Chiyoda-ku, Tokyo 102-0083, Japan
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Department of Human Wellness, Tokaigakuen University, 21-233 Nishinohora, Ukigai, Miyoshi, Aichi
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Correspondence:
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470-0207, Japan
Maya Hioki, PT, Ph.D.
Graduate School of Medicine, Nagoya University, 65 Tsurumai, Showa-ku, Nagoya, Aichi 466-8550, Japan Phone: +81(436)74-5908 Fax: +81(436)74-6400 E-mail [email protected] ORCID: 0000-0002-5276-4622 Conflict of interest: none Funding: A Grant-in-Aid for Challenging Exploratory Research from the Ministry of Education, Culture, Sports and Science and Technology Grant (#23650432) to HA. Support from the Descente and Ishimoto Memorial Foundation for the Promotion of Sport Science to YO
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Journal Pre-proof Abstract Whether age-related changes in muscle components differ between the quadriceps femoris and hamstrings has remained unclear. This study aimed to compare the muscle volume and echo intensity-estimated intramuscular adipose tissue content of the vastus lateralis (VL) and long head of biceps femoris (BF) muscles between young and older adults. Thirty young adults (n = 15; mean age, 21 years) and older adults (n = 15; mean age, 71 years) participated in this study. Magnetic resonance imaging was performed to determine muscle volumes of the VL and BF, and muscle volume normalized to body weight (muscle
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volume/weight). Mean gray-scale echo intensity was calculated as the intramuscular adipose tissue index.
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Muscle volume/weight and echo intensity were normalized using Z-scores in young and older adults.
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Muscle volume/weight was lower in older adults than in young adults, and lower in overall women than in men for VL (both p < 0.001) and BF (p < 0.01 and p < 0.05). Echo intensity was higher in older adults than
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in young adults for VL and BF (both p < 0.001), but did not differ between men and women. Z-score of
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muscle volume/weight was lower in older adults than in young adults for VL (-2.41 ± 1.22; p < 0.05), and Z-score of echo intensity was higher in older adults than in young adults for BF (2.00 ± 0.68; p < 0.05).
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These results suggest that muscle volume of quadriceps femoris was lower in older adults than in young
young adults.
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adults, whereas intramuscular adipose tissue content of hamstrings was greater in older adults than in
Key words: 1) muscle component, 2) muscle tissue, 3) adipose tissue, 4) magnetic resonance imaging, 5) ultrasonography
Abbreviations: BF, long head of biceps femoris; CT, computed tomography; DXA, dual-energy X-ray absorptiometry; EMCL, extramyocellular lipid; FCSA, fat cross-sectional area; HM, hamstrings; 1H-MRS, magnetic resonance spectroscopy; IMAT, intermuscular adipose tissue; IMCL, intramyocellular lipid; IntraMAT, intramuscular adipose tissue; mCSA, muscle cross-sectional area; MRI, magnetic resonance imaging; QF, quadriceps femoris; ROI, region of interest; SD, standard deviation; VL, vastus lateralis
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Journal Pre-proof Acknowledgments: This project was supported in part by a Grant-in-Aid for Challenging Exploratory Research from the Ministry of Education, Culture, Sports and Science and Technology Grant (#23650432) to HA and the Descente and Ishimoto Memorial Foundation for the Promotion of Sport Science to YO. We are grateful to Haruo Isoda, MD, Atsushi Fukuyama, PhD, and Akira Ishizuka, RT at the Nagoya University Brain & Mind Research Center, to Naoji Yasue, MD and Masumi Morita, RN at the Yasue Clinic, and to Yuko Shibata, PhD at the Nagoya University Sports Club for their assistance with this
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Journal Pre-proof 1. Introduction Loss of skeletal muscle mass with aging is one of the most widespread, deleterious, and insidious processes affecting the human body (Cartee et al., 2016). The reduction in thigh muscle mass has been interpreted as the primary reason for age-related loss of muscle function (i.e., sarcopenia) (Brooks and Faulkner 1994; Frontera et al., 1991; Lexell 1995). Indeed, age-related muscle dysfunction carries an increased risk of falls and limb fractures, and may result in a need for assistance with daily physical activities in older adults. Furthermore, ectopic adipose tissue infiltrates atrophied skeletal muscle with
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aging, as intramuscular adipose tissue (IntraMAT), and IntraMAT is independently associated with
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metabolic diseases, such as type 2 diabetes and obesity (Goodpaster et al., 1999; Goodpaster et al., 2000).
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Muscle atrophy with aging can be described as a multifactorial degenerative process impacted by cellular aging biology and environmental/behavioral (e.g., physical activity level) factors along with
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disease, but the mechanistic underpinnings remain poorly understood (Cartee et al., 2016). A
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cross-sectional study using magnetic resonance imaging (MRI), computed tomography (CT) and ultrasonography found that age-related changes in muscle component, i.e., muscle tissue decreases and
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IntraMAT accumulation, differ between individual muscles (Akima et al., 2015; Pillen and van Alfen 2011;
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Rice et al., 1989). According to previous studies, muscle atrophy appears greater in the lower limbs than in the upper limbs (Landers et al., 2001; Reimers 1998), particularly in the quadriceps femoris (QF) within the lower limb muscles. Preferential muscle atrophy of the QF with aging has been considered to result from its functional role in daily physical activities (i.e., as antigravity muscles). We therefore assumed that age-related reductions in muscle mass would differ between the QF and the antagonist muscle group of the hamstrings (HM). Although skeletal muscle possesses remarkable regenerative ability, in several pathological conditions where muscle integrity has been debilitated, skeletal muscle becomes occupied by adipocytes (Uezumi et al., 2010). Such excessive IntraMAT accumulation can be seen not only in type 2 diabetes (Goodpaster et al., 2003) and obesity (Goodpaster et al., 2000), but also as aging-related change (sarcopenia) (Akima et al., 2015). However, the origin of these adipocytes is unclear. In contrast, according to human studies, IntraMAT content is greater in HM compared with QF (Akima et al., 2015; Overend et al., 1992). This 5
Journal Pre-proof finding runs counter to the notion of excess IntraMAT content being associated with marked atrophy of muscles (i.e., QF). Whether age-related changes in muscle components such as adipose or muscle tissues differ between QF and HM remains unclear. Several non-invasive imaging techniques have been used to assess adipose tissues in muscle, such as MRI, CT, dual-energy X-ray absorptiometry (DXA), and ultrasonography. These imaging techniques have been established to offer high sensitivities and specificities, and have specific advantages and disadvantages. One advantage of both MRI and CT is the ability to visualize deeper muscles, but the major
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disadvantage of MRI is the cost, while CT has the disadvantage of requiring exposure of the patient to
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ionizing radiation. In ultrasonography, deeper structures (e.g., vastus intermedius as a deeper muscle) are
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more difficult to display because partial reflection of the ultrasound beam occurs when the sound beam encounters a different tissue (Pillen et al., 2008). However, ultrasonography remains a low-cost, easily
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accessible technology. Muscle components can be evaluated with muscle ultrasonography by measuring
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muscle echo intensity. Muscle echo intensity increases with age, potentially due to the age-related accumulation of adipose and fibrous tissues (Pillen et al., 2008).
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The purpose of this study was to compare muscle volume and echo intensity-estimated IntraMAT
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content of the quadriceps femoris (vastus lateralis [VL]) and hamstrings (long head of biceps femoris [BF]) between young and older adults using MRI and ultrasonography. We hypothesized that muscle volume and IntraMAT content in VL and BF would differ between young and older adults, due to differences in functional roles between QF and HM in daily physical activities.
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Journal Pre-proof 2. Materials and methods 2.1. Participants Fifteen physically active young individuals (8 men, 7 women) and 15 older individuals (7 men, 8 women) participated in this study. All subjects were living independently. The clinical histories of older adults were assessed using questionnaires. Older adults with a history of heart disease (myocardial infarction, angina pectoris, cardiac insufficiency), cerebrovascular disease (cerebral infarction, hemorrhage), extreme hypertension (systolic blood pressure ≥180 mmHg; diastolic blood pressure ≥110
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mmHg), or neuromuscular disorders were excluded. Moreover, none of the participants had any history of
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limb surgery. Young and older participants were recruited by university and local sports clubs designed
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specifically for older adults. The older adults had been participating once a week in local sports clubs designed for older individuals. All young and older individuals provided written informed consent prior to
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enrolment. This study was approved by the Ethics Committee of the Graduate School of Medicine Nagoya
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2.2. Magnetic resonance imaging
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University, and all protocols were in accordance with the guidelines in the Declaration of Helsinki.
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All participants refrained from participating in intense sport for 2 days before MRI. MRI was performed to acquire muscle volume using a 3.0 T MAGNETOM Verio (Siemens Healthcare GmbH, Eschborn, Germany) with a whole-body system to acquire muscle volume, muscle cross-sectional area (mCSA), and fat cross-sectional area (FCSA). We obtained a T1-weighted, spin-echo, axial-plane image (repetition time = 604 ms; echo time = 11 ms; matrix = 256 × 256; field of view = 256 mm; slice thickness = 10 mm; inter-slice gap = 0 mm) of the right thigh of participants in the morning. Participants were imaged in a supine position with pillows placed under the buttocks and leg to minimize tissue compression in the thigh. 2.2.1. Muscle volume, mCSA and fat cross-sectional area Muscle volume is considered the gold standard for estimating muscle size in humans. Muscle volume as determined from MRI was thus estimated as an index of muscle size. Muscle volumes of the VL and BF were estimated using 48 axial images from the right thigh, with the results transferred to a personal 7
Journal Pre-proof computer (Lets Note; Panasonic, Osaka, Japan) to estimate anatomical mCSAs from ImageJ software (version 1.47; National Institute of Health, Bethesda, MD). Muscle volume was determined by multiplying the sum of the mCSA of each image using the sum of thickness (10 mm) and inter-slice gap (0 mm) for each section. mCSA and fat cross-sectional area (FCSA) were determined from one image at the mid-thigh between the greater trochanter and lateral condyle of the femur, starting at the greater trochanter. A representative MRI for a young adult is shown in Figure 1. To minimize differences in body size, muscle volumes or mCSA of the VL and BF were normalized by body weight (muscle volume/weight and
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mCSA/weight).
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2.3. Ultrasonography
Ultrasonography scanning and analysis were performed by a single investigator (MH). Our study was
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not performed using a blinded method; therefore, ultrasonographic images were allocated serial numbers to
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prevent individual identification and were subsequently analyzed. All ultrasonography images were analyzed using Image J software. All participants refrained from participating in intense sport for 2 days
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before ultrasonography. Ultrasonographic measurements were performed twice, with an interval of at least
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1 week between measurements to test the reproducibility of the ultrasound technique. B-mode ultrasound scanning (LOGIQ e; GE Healthcare, Boston, MA) was performed by a single investigator. System-setting parameters were as follows: frequency, 8.0 MHz; gain, 80 dB; and depth, 8 cm. Participants were measured in the prone position with the leg fully extended and relaxed. Ultrasonographic images of the VL (lateral) and BF (posterior) were obtained at the mid-thigh between the greater trochanter and lateral condyle of the femur. All scans were made in the transverse plane with a linear transducer. An amount of contact gel was used to minimize the pressure of the transducer on the skin. Five images were scanned for each muscle. All images were stored in the ultrasonographic device in DICOM format for future analysis. 2.3.1. Muscle thickness and lateral or posterior subcutaneous thickness Muscle and subcutaneous tissue thicknesses were measured with electronic calipers placed at the middle of the ultrasound image (Fig. 2A, B). Muscle thickness was measured between the superficial and ventral muscle fascia, and subcutaneous tissue thickness was measured between the uppermost part of the 8
Journal Pre-proof skin and the superficial fascia of the muscle at the lateral and posterior sites. Three images were scanned for each part of the thigh, and these images were averaged for future analysis. To minimize the difference in body size, muscle thicknesses of the VL and BF were normalized by thigh length (muscle thickness/thigh length). 2.3.2. Intramuscular fat measurement by echo intensity Using echo intensity, as one of the indices reflecting IntraMAT in humans, intramuscular fat content was measured ultrasonographically. This was because our previous study clarified that echo intensity
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allows easy estimation of IntraMAT content in thigh muscles such VL (Akima et al., 2016). A region of
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interest (ROI) was selected in each of VL and BF, including as much of the muscle as possible on images,
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and bone and surrounding fascia were excluded. The smoothing function was applied to decrease noise in the ROI. Mean echo intensity of the ROI was calculated (8-bit resolution, resulting in a number between 0
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and 255, where black = 0, white = 255) (Fig. 2A, B). Mean echo intensity within the ROI in five images
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was measured for each muscle. To minimize variations in echo intensity due to technical errors, images with highest and lowest values of echo intensity were excluded. The remaining echo intensity in three
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images was averaged for future analysis. The mean coefficient of variation of the first and second
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measurements was 9.4 ± 8.6% in the VL and 5.7 ± 4.8% in the BF (at system setting parameter gain 80 dB) (n = 30 each). Coefficients of variation for VL and BF (> 10%) were fair, compared with the mean coefficients of variation reported by Young et al. (rectus femoris [RF], 5.6%; BF, 5.0%) (Young et al., 2015) and Scholten et al. (RF, 7.3%) (Scholten et al., 2003). Our previous study (Akima et al., 2016) showed that echo intensity correlated significantly with IntraMAT content of the VL and BF on MRI (VL, r = 0.404, p < 0.05; BF, r = 0.493, p < 0.01), and correlated significantly with EMCL of VL and BF by 1H-MRS (VL, r = 0.485, p < 0.05; BF, r = 0.648, p < 0.01).
2.4. Physical activity levels and dietary habits Physical activity levels were matched between young and older adults. The physical activity level was estimated from the records of the three-dimensional ambulatory accelerometer (Lifecorder; Suzuken Co., 9
Journal Pre-proof Nagoya, Japan) for 10 days. Habitual dietary intake was estimated using a food frequency questionnaire (Perez Rodrigo et al., 2015). The questionnaire asked about the average intake and frequency of consumption of each food. Dietary assessment indicated the energy (kcal/body weight), carbohydrate (g/body weight), protein (g/body weight), and fat (g/body weight) intakes for the dietary habits. Physical activity and habitual dietary intake details in young and older adults are shown in our previous studies (Hioki et al., 2019).
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2.5. Z score calculation
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Muscle volume, muscle volume normalized to body weight (muscle volume/weight), and echo
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intensity were normalized using Z-scores with individual data expressed as the number of standard deviations (SDs) from the mean for the young adult, calculated as: χ−μ σ
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𝑍=
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where χ is the value for individual adults, and μ and σ are the mean and SD, respectively, of the
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2.6. Statistics
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corresponding young adults (Maden-Wilkinson et al., 2014).
Data are expressed as mean ± SD. All data were compared using a two-way analysis of variance (ANOVA) with aging and sex as the between-group effects. Differences in muscle volume and echo intensity between VL and BF were evaluated using two-way ANOVA with aging and muscles. When a significant interaction effect was obtained, Bonferroni significant difference post-hoc analysis was utilized to determine specific differences. As the standard in the young adult, the Z-score was set to ± 2 SD (95% confidence interval) for muscle volume, muscle volume/weight, and echo intensity. The relationship between VL and BF in muscle volume or echo intensity, and the relationship between muscle volume/weight and echo intensity were determined using Pearson’s correlations analysis. Statistical significance was defined as p < 0.05. All statistical analyses were performed using SPSS version 24.0 software (SPSS Inc., Chicago, IL).
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Parts of the data have been reported previously. Those parts focused on different topics (extramyocellular lipid [EMCL] or intramuscular fat content as determined from MRI (Akima et al., 2016; Akima et al., 2015; Yoshiko et al., 2017) and intramyocellular lipid [IMCL] by 1H-magnetic resonance spectroscopy [1H-MRS]) (Hioki et al., 2016; Hioki et al., 2019), in contrast with the present topic
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(IntraMAT content by ultrasound).
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Journal Pre-proof 3. Results 3.1. Participant characteristics The characteristics of the participants are provided in Table 1. Overall, men were higher and heavier than women and young adults were higher and heavier than older adults. FCSA was higher overall in women than in men and higher in young women than in older women, but did not differ between young men and older men. In the older group, four participants had type 2 diabetes. Among these four participants with type 2
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diabetes, one was medicated with an -glucosidase inhibitor and thiazolidinedione, one with a dipeptidyl
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peptidase inhibitor, and two with metformin.
3.2. Muscle profiles
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The characteristics of muscle profiles are provided in Table 1. Muscle volume/weight was lower in
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older adults than in young adults, and lower in overall women than in men for VL and BF. Echo intensity was higher in older adults than in young adults for VL and BF, but did not differ between men and women.
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Regarding inter-muscle difference of muscle profiles, muscle volume of BF was significantly lower
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and echo intensity of BF was significantly higher than VL in older and young adults, respectively (p <
3.3. Physical activity level and dietary habits Characteristics of physical activity level and dietary intake habits are provided in Table 2. Physical activity level was not significantly different between young and older adults, and was not different overall between men and women. Regarding habitual dietary intake, protein intake was significantly higher in older adults than in young adults, but energy, carbohydrate and fat intake did not differ significantly between young and older adults. Energy, carbohydrate, protein and fat were significantly higher overall in women than in men.
3.4. Z-score 12
Journal Pre-proof Table 3 and Figure 3 show the Z-score in muscle volume, muscle volume/weight, and echo intensity for VL and BF of the young and older adults. Mean Z-score of the muscle volume/weight in older adults was 2 SD below the mean Z-score in young adults for VL (Fig. 3C), and that of the mean Z-score of the echo intensity in older adults was 2 SD above the mean Z-score in young adults for BF (Fig. 3F) (p < 0.05 each). In contrast, such a significant difference was not observed for muscle volume in VL and BF (Fig. 3A, B), or muscle volume/weight in BF (Fig. 3D) and echo intensity in VL (Fig. 3E).
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3.5. Correlations between VL and BF in muscle volume and echo intensity
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Figure 4 shows correlations between VL and BF in muscle volume, echo intensity of the young and
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older adults. A significant correlation was seen between VL and BF in muscle volume (r = 0.86, p < 0.001) (Fig. 4A) and echo intensity (r = 0.70, p < 0.01) (Fig. 4C) in the young adults. A significant correlation was
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seen between VL and BF in muscle volume (r = 0.65, p < 0.01) (Fig. 4B), but no relationship between VL
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and BF in echo intensity was observed in older adults (Fig. 4D).
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3.6. Correlations between muscle volume/weight and echo intensity in VL and BF
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Figure 5 shows correlations between muscle volume/weight and echo intensity in VL and BF of the young and older adults. A relationship between muscle volume/weight and echo intensity in VL and BF was not observed in young adults (Fig. 5A, C) or older adults (Fig. 5B, D).
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Journal Pre-proof 4. Discussion Our results support the hypothesis that muscle volume and echo intensity-estimated IntraMAT content in VL and BF differ between young and older adults. Muscle volume/weight was relatively lower in older adults than in young adults for VL, and echo intensity was relatively higher in older adults than in young adults for BF. A significant relationship was found between VL and BF in muscle volume of the young as well as in that of older adults, and a significant relationship was found between VL and BF in echo intensity of young adults, but not that of older adults. These results suggest that muscle volume of QF is
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less in older adults than in young adults, whereas the IntraMAT content of HM is greater in older adults
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than in young adults, and IntraMAT content correlated between QF and HM muscles in young adults, but
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not in older adults.
According to several studies, mCSA was lower in older male adults than in young male adults for QF
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(-14%) (Nilwik et al., 2013), and muscle volume was lower in older men than in young male and female
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adults for QF (-26.5%) (Hogrel et al., 2015), so the difference in mCSA is smaller compared with muscle volume. Our results also indicated differences in muscle volume/weight (VL, -29.3%; BF, -13.5%),
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mCSA/weight (VL, -24.2%; BF, -5.6%), and muscle thickness/thigh length (VL, -6.4%; BF, -3.8%).
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Roman et al. (Roman et al., 1993) reported that muscle volume, rather than mCSA or muscle thickness, is the most accurate measure for estimating muscle size. Our study therefore accurately measured age-related changes in muscle mass. Moreover, we used Z-scores to clearly judge the difference between older and young adults, showing that Z-scores for muscle volume/weight in VL were lower in older adults than in young adults (2 SD below the young adult mean). The loss in muscle strength of the lower extremity is greater than that of the upper extremity, presumably due to decreasing use of the lower limbs compared with upper limb muscles in older adults, and suggesting the main cause as muscle atrophy with aging (Frontera et al., 1991). Although total physical activity levels were similar between young and older adults, vigorous intensity physical activity level was lower in older adults than in young adults (Hioki et al., 2019). Age-related reductions in muscle mass might thus differ between QF and its antagonist muscle group (i.e., HM). However, the mechanisms underlying sarcopenia (loss of muscle mass) involve endocrine abnormalities, neuro-degenerative diseases, inadequate nutrition malabsorption, cachexia, and disuse 14
Journal Pre-proof (Cruz-Jentoft et al., 2010), among others, and we thus speculate that not only physical inactivity, but also multiple other factors might interact. We found that echo intensity was higher in BF than in VL in older adults as well as young adults, and changes in echo intensity between young and older adults were similar in VL (35.2%) as well as BF (33.6%). These results indicate that IntraMAT accumulation might be greater than the reduction in muscle volume with aging. Moreover, the Z-score of echo intensity in BF was higher in older adults than in young adults, and echo intensity was higher in BF than in VL among older adults in this study. Older individuals
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with increased IntraMAT in the lower limb muscles are known to show increased levels of muscle
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weakness, and decreased mobility limitation (Goodpaster et al., 2001; Visser et al., 2005; Visser et al.,
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2002). Although studies have focused on age-related changes in QF components, such age-related changes in muscle components might influence QF as well as HM functions in older adults. One effective approach
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to rehabilitation could thus be to decrease IntraMAT for thigh muscles (particularly, HM) in older adults.
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We found a significant relationship between echo intensity of VL and BF in young adults. Our results agreed with those reported by Young et al. (Young et al., 2016). Such evidence indicates a significant
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correlation between RF and BF for echo intensity-estimated IntraMAT content in adults (age range, 19-68
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years), suggesting that the characteristic IntraMAT content is similar in all muscles (Young et al., 2016). However, no such correlation was observed for older adults in the present study. Our findings suggest that IntraMAT accumulation in the leg cannot be characterized from a single muscle, especially when determining age-related changes in muscle components in older adults. Our results thus suggest that IntraMAT accumulation with aging is independent of muscle. Previous studies have reported that muscle attenuation correlated inversely with increased IntraMAT content (as measured using CT) in the thigh and calf muscles among young and older adults, subjects with type 2 diabetes (Goodpaster et al., 2000) and obesity (Tuttle et al., 2012). These results indicate that IntraMAT might infiltrate atrophied muscle. Furthermore, an animal study indicated that fat accumulation and fibrosis might lead to muscle atrophy (loss of muscle content) (Uezumi et al., 2011). However, our results indicated that no relationship existed between muscle volume and echo intensity in the muscles of both young and older adults. According to our previous study (Akima et al., 2015), IntraMAT content 15
Journal Pre-proof correlated with mCSA in some, but not all, muscle groups for both young and older groups (QF, HM, and adductors). These results suggest that atrophied muscle (lower muscle mass) in individuals seems essential for IntraMAT accumulation. Furthermore, Manini et al. (Manini et al., 2007) reported that as a result of 30 days of unilateral limb unloading, young healthy adults experienced a 15-20% increase in intermuscular adipose tissue (IMAT) of both the calf and thigh muscles, and this increase in IMAT exceeded the loss of lean tissue. These results indicate that IMAT might not just merely fill the space of lost muscle tissue. Age-related changes in muscle mass and IMAT or IntraMAT accumulation might not be tightly linked.
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Thus, such correlations might not be observed in older and young adults.
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This study has some limitations that need to be considered when interpreting the results. Our findings
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(estimated IntraMAT content by echo intensity) agree with a previous study that used MRI and 1H-MRS to estimate IntraMAT content. According to previous studies (Akima et al., 1997; Narici et al., 1989) using
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MRI, the change in the individual muscles of the lower thigh differs along the longitudinal axis of the thigh
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after physical inactivity or resistance exercise. These previous studies suggest that a single site and single muscle measurement for determining muscle size may lead to inaccurate estimates where changes in
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muscle size occur on MRI as well as ultrasonography. Ultrasonography has been widely used to evaluate
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atrophic muscle and echo intensity estimated-IntraMAT content in both study and clinical settings. However, muscle mass or IntraMAT content is estimated from part of the muscle in a narrow range of ultrasonographic images. Quantity and quality of thigh muscle are important for carrying out activities of daily living, and careful measurements are needed to achieve accurate estimates, especially QF and HM. We estimated IntraMAT content from echo intensity obtained from ultrasonography. However, echo intensity-estimated IntraMAT contains not only intramuscular adipose tissue, but also lipomatosis and fibrosis. Lipomatosis and fibrosis are unable to be completely removed. When sound is transmitted through tissue, attenuation of the ultrasound beam occurs because of reflection, dispersion, and absorption of the soundwaves (Pillen et al., 2008). Echo intensity thus reduces with depth. Higher subcutaneous fat thickness shows reduced echo intensity as depth increases. Sarcopenia is defined as muscle size falling below some lower limit, often defined as -2 SD below the values for young adults. Cutoffs set at 2 SD below the mean of a healthy, young adult population were recommended by the European Working Group 16
Journal Pre-proof on Sarcopenia in Older People (Cruz-Jentoft et al., 2010; Cruz-Jentoft et al., 2019). Maden-Wilkinson et
al. (2014) also used cutoffs set at 2 SD to determine sarcopenia. Therefore, our study also used cutoffs set at 2 SD. However, our study did not perform any a priori calculation of sample size. Our findings are thus better suited to hypothesis generation than precise determination of etiology.
5. Conclusion We assessed muscle volume and echo intensity-estimated IntraMAT in the QF and HM with different
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functional roles in daily physical activities by MRI and ultrasonography. These results suggest that muscle
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volume of QF is less in older than in young adults, whereas the IntraMAT content of HM is greater in older
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adults than in young adults, and IntraMAT accumulation was related between QF and HM muscles in young, but not in older adults. Assessment of IntraMAT accumulation thus needs to consider not only
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aging, but also the specific muscle. For the examination of muscle components, ultrasonography is easy
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and less expensive compared with MRI, CT, and DXA. Echo intensity-estimated IntraMAT could be helpful for rehabilitation professionals for evaluating aging muscle in rehabilitation and clinical settings.
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The degree to which these results can be generalized as a definition of sarcopenia (decrease in muscle size
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and increase in IntraMAT) is unclear, but warrants examination.
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Journal Pre-proof Declarations of interest
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The authors declare that they have no conflicts of interest.
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References
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older women. J Gerontol A Biol Sci Med Sci. 56:B443-448; 2001 Lexell, J. Human aging, muscle mass, and fiber type composition. J Gerontol A Biol Sci Med Sci. 50:11-16; 1995 Maden-Wilkinson, T.M.; McPhee, J.S.; Rittweger, J.; Jones, D.A.; Degens, H. Thigh muscle volume in relation to age, sex and femur volume. Age (Dordr). 36:383-393; 2014 Manini, T.M.; Clark, B.C.; Nalls, M.A.; Goodpaster, B.H.; Ploutz-Snyder, L.L.; Harris, T.B. Reduced physical activity increases intermuscular adipose tissue in healthy young adults. Am J Clin Nutr. 85:377-384; 2007 Narici, M.V.; Roi, G.S.; Landoni, L.; Minetti, A.E.; Cerretelli, P. Changes in force, cross-sectional area and neural activation during strength training and detraining of the human quadriceps. Eur J Appl Physiol Occup Physiol. 59:310-319; 1989 Nilwik, R.; Snijders, T.; Leenders, M.; Groen, B.B.; van Kranenburg, J.; Verdijk, L.B.; van Loon, L.J. The decline in skeletal muscle mass with aging is mainly attributed to a reduction in type II muscle fiber size. Exp Gerontol. 48:492-498; 2013 Overend, T.J.; Cunningham, D.A.; Paterson, D.H.; Lefcoe, M.S. Thigh composition in young and elderly men determined by computed tomography. Clin Physiol. 12:629-640; 1992 Perez Rodrigo, C.; Aranceta, J.; Salvador, G.; Varela-Moreiras, G. Food frequency questionnaires. Nutr Hosp. 31 Suppl 3:49-56; 2015 Pillen, S.; Arts, I.M.P.; Zwarts, M.J. Muscle ultrasound in neuromuscular disorders. Muscle Nerve. 37:679-693; 2008 Pillen, S.; van Alfen, N. Skeletal muscle ultrasound. Neurol Res. 33:1016-1024; 2011 Reimers, C.D., Harder, T., Saxe, H. Age-related muscle atrophy does not affect all muscles and can partly be compensated by physical activity: an ultrasound study. J Neurol Sci. 159: 60-66; 1998 Rice, C.L.; Cunningham, D.A.; Paterson, D.H.; Lefcoe, M.S. Arm and leg composition determined by computed tomography in young and elderly men. Clin Physiol. 9:207-220; 1989 Roman, W.J.; Fleckenstein, J.; Stray-Gundersen, J.; Alway, S.E.; Peshock, R.; Gonyea, W.J. Adaptations in the elbow flexors of elderly males after heavy-resistance training. J Appl Physiol. 74:750-754; 1993 Scholten, R.R.; Pillen, S.; Verrips, A.; Zwarts, M.J. Quantitative ultrasonography of skeletal muscles in children: normal values. Muscle Nerve. 27:693-698; 2003 Tuttle, L.J.; Sinacore, D.R.; Mueller, M.J. Intermuscular adipose tissue is muscle specific and associated with poor functional performance. Journal of aging research. 2012:172957; 2012 Uezumi, A.; Fukada, S.; Yamamoto, N.; Takeda, S.; Tsuchida, K. Mesenchymal progenitors distinct from satellite cells contribute to ectopic fat cell formation in skeletal muscle. Nat Cell Biol. 12:143-152; 2010 Uezumi, A.; Ito, T.; Morikawa, D.; Shimizu, N.; Yoneda, T.; Segawa, M.; Yamaguchi, M.; Ogawa, R.; Matev, M.M.; Miyagoe-Suzuki, Y.; Takeda, S.; Tsujikawa, K.; Tsuchida, K.; Yamamoto, H.; Fukada, S. Fibrosis and adipogenesis originate from a common mesenchymal progenitor in skeletal muscle. J Cell Sci. 124:3654-3664; 2011 Visser, M.; Goodpaster, B.H.; Kritchevsky, S.B.; Newman, A.B.; Nevitt, M.; Rubin, S.M.; Simonsick, E.M.; Harris, T.B. Muscke mass, muscle strength, and muscle fat infiltration as predictors of incident mobility limitations on well-functioning or older persons. J Gerontol A Biol Sci Med Sci. 60:324-333; 2005 Visser, M.; Kritchevsky, S.B.; Goodpaster, B.H.; Newman, A.B.; Nevitt, M.; Stamm, E.; Harris, T.B. Leg muscle mass and composition in relation to lower extremity performance in men and women aged 70 to 79: the health, aging and body composition study. J Am Geriatr Soc. 50:897-904; 2002 Yoshiko, A.; Hioki, M.; Kanehira, N.; Shimaoka, K.; Koike, T.; Sakakibara, H.; Oshida, Y.; Akima, H. Three-dimensional comparison of intramuscular fat content between young and old adults. BMC 20
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medical imaging. 17:12; 2017 Young, H.J.; Jenkins, N.T.; Zhao, Q.; McCully, K.K. Measurement of intramuscular fat by muscle echo intensity. Muscle Nerve. 52:963-971; 2015 Young, H.J.; Southern, W.M.; McCully, K.K. Comparisons of ultrasound-estimated intramuscular fat with fitness and health indicators. Muscle Nerve. 54:743-749; 2016
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Journal Pre-proof Figure captions Fig. 1 Representative T1-weighted MRIs from a 21-year-old man. Dotted line indicates mCSA (A) and FCSA (B) at the mid-thigh. AM, adductor magnus; BF, long head of biceps femoris; BFs, short head of biceps femoris; Gr, gracilis; RF, rectus femoris; Sar, sartorius; SM, semimembranosus; ST, semitendinosus; VI, vastus intermedius; VM, vastus medialis; VL, vastus lateralis
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Fig. 2
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Representative ultrasonography images and MRIs demonstrate the same muscle site. Example of
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ultrasonographic scans of vastus lateralis (A) and long head of biceps femoris (B). These figures show an ultrasonographic image (left), a graphic representation of the scan (middle), and an MRI (above right).
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Dotted line in the middle panel indicates the region of interest (ROI) for echo intensity, and muscle and
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subcutaneous tissue thicknesses are indicated by dotted arrows. The bottom right panel indicates the ROI with gray-scale histograms. Ultrasonography was performed with the subject in the prone position, and
Fig. 3
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MRI was performed with the subject in the supine position
Comparison of muscle profile z-scores in young and older adults. Mean values for young adults (0, solid line) and ± 2 SD (dotted lines) are shown. BF, long head of biceps femoris; VL, vastus lateralis
Fig. 4 Pearson correlation coefficients for correlations between VL and BF in muscle volume normalized to body weight, echo intensity in the young (A and C) and older adults (B and D). a.u., arbitrary units; BF, long head of biceps femoris; VL, vastus lateralis
Fig. 5 Pearson correlation coefficients for correlations between muscle volume normalized to body weight and 22
Journal Pre-proof echo intensity from VL and BF in young (A and C) and older adults (B and D). a.u., arbitrary units; BF,
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long head of biceps femoris; VL, vastus lateralis
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Journal Pre-proof Author Statement
Maya Hioki: Methodology, Validation, Investigation, Data Curation, Writing - Original Draft, Formal analysis Nana Kanehira: Validation, Investigation, Data Curation Teruhiko Koike: Visualization, Writing - Review & Editing Akira Saito: Formal analysis, Investigation, Writing - Original Draft
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Kiyoshi Shimaoka: Resources
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Hisataka Sakakibara: Writing - Review & Editing
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Yoshiharu Oshida: Funding acquisition, Project administration
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Hiroshi Akima: Funding acquisition, Supervision, Conceptualization
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Journal Pre-proof Table 1 Participant characteristics young Men
older women
Men
women
% differ
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No. of participants 8 7 7 8 Physical characteristics Age (year) 21.0 ± 0.0 21.0 ± 0.0 71.1 ± 4.8 70.4 ± 2.9 Height (cm) 176.0 ± 6.5 157.3 ± 3.5 163.0 ± 2.7 152.1 ± 3.5 Weight (kg) 67.8 ± 8.0 55.9 ± 10.6 61.4 ± 4.5 50.9 ± 6.6 Thigh length (cm) 38.7 ± 1.3 33.8 ± 1.2 35.2 ± 1.3 32.2 ± 0.8 2 BMI (kg/m ) 21.9 ± 1.8 22.5 ± 3.5 23.1 ± 1.0 22.0 ± 2.7 2 FCSA (cm ) 40.0 ± 15.7 85.1 ± 23.5 35.5 ± 8.7 55.5 ± 13.7 Lateral subcutaneous thickness 0.4 ± 0.2 1.3 ± 0.4 0.5 ± 0.2 0.8 ± 0.3 (cm) Posterior subcutaneous 0.6 ± 0.3 1.4 ± 0.3 0.6 ± 0.2 0.7 ± 0.2 thickness (cm) Muscle profiles VL 3 Muscle volume (cm ) 535.5 ± 49.1 366.9 ± 60.3 369.4 ± 35.0 223.3 ± 37.1 -36.2 2 mCSA (cm ) 23.1 ± 2.2 18.7 ± 3.1 18.3 ± 1.8 11.1 ± 1.5 -31.1 Muscle thickness (cm) 1.9 ± 0.4 1.8 ± 0.3 1.7 ± 0.3 1.5 ± 0.4 -13.6 Muscle volume/weight 7.9 ± 0.6 6.6 ± 0.5 6.0 ± 0.7 4.4 ± 0.7 -29.3 mCSA/weight 0.34 ± 0.04 0.34 ± 0.04 0.30 ± 0.03 0.22 ± 0.04 -24.2 Muscle thickness/thigh length 0.05 ± 0.01 0.05 ± 0.01 0.05 ± 0.01 0.05 ± 0.01 -6.4 Echo intensity (a.u.) 54.5 ± 13.1 49.1 ± 5.8 69.8 ± 8.9 70.8 ± 9.6 +35.2 BF 3 Muscle volume (cm ) 176.2 ± 22.2 117.7 ± 27.3 128.9 ± 17.2 102.8 ± 17.7 -22.8 2 mCSA (cm ) 10.6 ± 1.3 8.8 ± 2.5 8.9 ± 1.1 7.8 ± 1.1 -15.4 Muscle thickness (cm) 2.1 ± 0.2 2.0 ± 0.3 2.0 ± 0.2 1.7 ± 0.3 -10.8 Muscle volume/weight 2.6 ± 0.3 2.1 ± 0.3 2.1 ± 0.3 2.0 ± 0.2 -13.5 mCSA/weight 0.16 ± 0.02 0.16 ± 0.03 0.14 ± 0.02 0.15 ± 0.02 -5.6 Muscle thickness/thigh length 0.05 ± 0.01 0.06 ± 0.01 0.06 ± 0.00 0.05 ± 0.01 -3.8 Echo intensity (a.u.) 65.0 ± 14.8 61.9 ± 2.2 82.7 ± 5.3 86.9 ± 8.5 +33.6 Value are means ± SD. a.u., arbitrary units; BF, long head of biceps femoris; BMI, body mass index; FCSA, fat cross-sectional area; mCSA, muscle cross-sectional area; VL, vastus lateralis. Data for older adults are expressed as a percentage of the difference value for young adults. All participants were the same as those previously reported by Akima et al. (2015, 2016), Hioki et al. (2016, 2019) and Yoshiko et al. (2017)
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Age effect
0.000 0.054 0.000 0.704 0.008 0.025 0.000
0.000 0.000 0.074 0.000 0.000 0.404 0.000 0.001 0.022 0.015 0.009 0.282 0.343 0.000
Journal Pre-proof Table 2 Physical activity and habitual dietary characteristics young Men women No. of participants Physical activity levels (kcal/day)
8 304.8 ± 90.2
older
7 223.2 105.5
±
men
women
Age effect
7 203.8 ± 62.6
8 235.2 ± 88.2
0.179
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Habitual dietary intake Energy (kcal/body weight) 26.0 ± 6.5 32.4 ± 12.1 30.3 ± 4.4 35.3 ± 4.7 Carbohydrate (g/body weight) 3.5 ± 0.8 4.3 ± 1.5 4.0 ± 0.6 4.7 ± 0.8 Protein (g/body weight) 0.8 ± 0.3 1.1 ± 0.4 1.1 ± 0.3 1.4 ± 0.2 Fat (g/ body weight) 0.8 ± 0.3 1.1 ± 0.4 0.9 ± 0.3 1.2 ± 0.3 Value are means ± SD. All participants were the same as those previously reported by Akima et al. (2015, 2016), Hioki et al. (2016, 2019) and Yoshiko et al. (2017)
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0.190 0.222 0.010 0.717
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Table 3 Z scores of muscle component in young and older adults Young Older (n = 15) (n = 15) Muscle volume/weight VL 0±1 -2.41 ± 1.22* BF 0±1 -0.79 ± 0.62 Muscle volume VL 0±1 -1.63 ± 0.82 BF 0±1 -0.88 ± 0.56 Echo intensity VL 0±1 1.77 ± 0.86 BF 0±1 2.00 ± 0.68* * , p< 0.05 (significant ±2 SD); mean ± SD. BF, long head of biceps femoris; VL, vastus lateralis
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Journal Pre-proof Highlights
・ Muscle volume of quadriceps femoris is less in older than in young adults. ・ Intramuscular adipose tissue content of hamstrings is greater in older adults than in young adults. ・ Intramuscular adipose tissue accumulation was related between quadriceps femoris and hamstrings
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muscles in young, but not in older adults.
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Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Maya Hioki, Nana Kanehira, Teruhiko Koike, Akira Saito, Kiyoshi Shimaoka, Hisataka Sakakibara, Yoshiharu Oshida, Hiroshi Akima PII:
S0531-5565(19)30508-X
DOI:
https://doi.org/10.1016/j.exger.2020.110834
Reference:
EXG 110834
To appear in:
Experimental Gerontology
Received date:
24 July 2019
Revised date:
3 January 2020
Accepted date:
6 January 2020
Please cite this article as: M. Hioki, N. Kanehira, T. Koike, et al., Age-related changes in muscle volume and intramuscular fat content in quadriceps femoris and hamstrings, Experimental Gerontology(2018), https://doi.org/10.1016/j.exger.2020.110834
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© 2018 Published by Elsevier.
Journal Pre-proof Age-related changes in muscle volume and intramuscular fat content in quadriceps femoris and hamstrings
Maya Hiokia, Nana Kanehirab, Teruhiko Koikec, Akira Saitod, e, Kiyoshi Shimaokaf, Hisataka Sakakibaraa, Yoshiharu Oshidac, Hiroshi Akimac
a
Graduate School of Medicine, Nagoya University, 65 Tsurumai, Showa-ku, Nagoya, Aichi 466-8550,
Japan Department of Health and Nutrition, Tokaigakuen University, 2-901 Nakahira, Tenpaku, Nagoya, Aichi
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Research Center of Health, Physical Fitness & Sports, Nagoya University, 1 Furo, Chikusa-ku, Nagoya,
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468-8514, Japan
Aichi 464-8601, Japan
Graduate School of Arts and Sciences, College of Arts and Sciences, University of Tokyo, Komaba 3-8-1
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Meguro-ku, Tokyo 153-8092, Japan
Japan Society for the Promotion of Science, Kojimachi, Chiyoda-ku, Tokyo 102-0083, Japan
f
Department of Human Wellness, Tokaigakuen University, 21-233 Nishinohora, Ukigai, Miyoshi, Aichi
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e
Correspondence:
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470-0207, Japan
Maya Hioki, PT, Ph.D.
Graduate School of Medicine, Nagoya University, 65 Tsurumai, Showa-ku, Nagoya, Aichi 466-8550, Japan Phone: +81(436)74-5908 Fax: +81(436)74-6400 E-mail [email protected] ORCID: 0000-0002-5276-4622 Conflict of interest: none Funding: A Grant-in-Aid for Challenging Exploratory Research from the Ministry of Education, Culture, Sports and Science and Technology Grant (#23650432) to HA. Support from the Descente and Ishimoto Memorial Foundation for the Promotion of Sport Science to YO
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Journal Pre-proof Abstract Whether age-related changes in muscle components differ between the quadriceps femoris and hamstrings has remained unclear. This study aimed to compare the muscle volume and echo intensity-estimated intramuscular adipose tissue content of the vastus lateralis (VL) and long head of biceps femoris (BF) muscles between young and older adults. Thirty young adults (n = 15; mean age, 21 years) and older adults (n = 15; mean age, 71 years) participated in this study. Magnetic resonance imaging was performed to determine muscle volumes of the VL and BF, and muscle volume normalized to body weight (muscle
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volume/weight). Mean gray-scale echo intensity was calculated as the intramuscular adipose tissue index.
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Muscle volume/weight and echo intensity were normalized using Z-scores in young and older adults.
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Muscle volume/weight was lower in older adults than in young adults, and lower in overall women than in men for VL (both p < 0.001) and BF (p < 0.01 and p < 0.05). Echo intensity was higher in older adults than
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in young adults for VL and BF (both p < 0.001), but did not differ between men and women. Z-score of
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muscle volume/weight was lower in older adults than in young adults for VL (-2.41 ± 1.22; p < 0.05), and Z-score of echo intensity was higher in older adults than in young adults for BF (2.00 ± 0.68; p < 0.05).
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These results suggest that muscle volume of quadriceps femoris was lower in older adults than in young
young adults.
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adults, whereas intramuscular adipose tissue content of hamstrings was greater in older adults than in
Key words: 1) muscle component, 2) muscle tissue, 3) adipose tissue, 4) magnetic resonance imaging, 5) ultrasonography
Abbreviations: BF, long head of biceps femoris; CT, computed tomography; DXA, dual-energy X-ray absorptiometry; EMCL, extramyocellular lipid; FCSA, fat cross-sectional area; HM, hamstrings; 1H-MRS, magnetic resonance spectroscopy; IMAT, intermuscular adipose tissue; IMCL, intramyocellular lipid; IntraMAT, intramuscular adipose tissue; mCSA, muscle cross-sectional area; MRI, magnetic resonance imaging; QF, quadriceps femoris; ROI, region of interest; SD, standard deviation; VL, vastus lateralis
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Journal Pre-proof Acknowledgments: This project was supported in part by a Grant-in-Aid for Challenging Exploratory Research from the Ministry of Education, Culture, Sports and Science and Technology Grant (#23650432) to HA and the Descente and Ishimoto Memorial Foundation for the Promotion of Sport Science to YO. We are grateful to Haruo Isoda, MD, Atsushi Fukuyama, PhD, and Akira Ishizuka, RT at the Nagoya University Brain & Mind Research Center, to Naoji Yasue, MD and Masumi Morita, RN at the Yasue Clinic, and to Yuko Shibata, PhD at the Nagoya University Sports Club for their assistance with this
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Journal Pre-proof 1. Introduction Loss of skeletal muscle mass with aging is one of the most widespread, deleterious, and insidious processes affecting the human body (Cartee et al., 2016). The reduction in thigh muscle mass has been interpreted as the primary reason for age-related loss of muscle function (i.e., sarcopenia) (Brooks and Faulkner 1994; Frontera et al., 1991; Lexell 1995). Indeed, age-related muscle dysfunction carries an increased risk of falls and limb fractures, and may result in a need for assistance with daily physical activities in older adults. Furthermore, ectopic adipose tissue infiltrates atrophied skeletal muscle with
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aging, as intramuscular adipose tissue (IntraMAT), and IntraMAT is independently associated with
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metabolic diseases, such as type 2 diabetes and obesity (Goodpaster et al., 1999; Goodpaster et al., 2000).
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Muscle atrophy with aging can be described as a multifactorial degenerative process impacted by cellular aging biology and environmental/behavioral (e.g., physical activity level) factors along with
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disease, but the mechanistic underpinnings remain poorly understood (Cartee et al., 2016). A
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cross-sectional study using magnetic resonance imaging (MRI), computed tomography (CT) and ultrasonography found that age-related changes in muscle component, i.e., muscle tissue decreases and
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IntraMAT accumulation, differ between individual muscles (Akima et al., 2015; Pillen and van Alfen 2011;
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Rice et al., 1989). According to previous studies, muscle atrophy appears greater in the lower limbs than in the upper limbs (Landers et al., 2001; Reimers 1998), particularly in the quadriceps femoris (QF) within the lower limb muscles. Preferential muscle atrophy of the QF with aging has been considered to result from its functional role in daily physical activities (i.e., as antigravity muscles). We therefore assumed that age-related reductions in muscle mass would differ between the QF and the antagonist muscle group of the hamstrings (HM). Although skeletal muscle possesses remarkable regenerative ability, in several pathological conditions where muscle integrity has been debilitated, skeletal muscle becomes occupied by adipocytes (Uezumi et al., 2010). Such excessive IntraMAT accumulation can be seen not only in type 2 diabetes (Goodpaster et al., 2003) and obesity (Goodpaster et al., 2000), but also as aging-related change (sarcopenia) (Akima et al., 2015). However, the origin of these adipocytes is unclear. In contrast, according to human studies, IntraMAT content is greater in HM compared with QF (Akima et al., 2015; Overend et al., 1992). This 5
Journal Pre-proof finding runs counter to the notion of excess IntraMAT content being associated with marked atrophy of muscles (i.e., QF). Whether age-related changes in muscle components such as adipose or muscle tissues differ between QF and HM remains unclear. Several non-invasive imaging techniques have been used to assess adipose tissues in muscle, such as MRI, CT, dual-energy X-ray absorptiometry (DXA), and ultrasonography. These imaging techniques have been established to offer high sensitivities and specificities, and have specific advantages and disadvantages. One advantage of both MRI and CT is the ability to visualize deeper muscles, but the major
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disadvantage of MRI is the cost, while CT has the disadvantage of requiring exposure of the patient to
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ionizing radiation. In ultrasonography, deeper structures (e.g., vastus intermedius as a deeper muscle) are
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more difficult to display because partial reflection of the ultrasound beam occurs when the sound beam encounters a different tissue (Pillen et al., 2008). However, ultrasonography remains a low-cost, easily
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accessible technology. Muscle components can be evaluated with muscle ultrasonography by measuring
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muscle echo intensity. Muscle echo intensity increases with age, potentially due to the age-related accumulation of adipose and fibrous tissues (Pillen et al., 2008).
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The purpose of this study was to compare muscle volume and echo intensity-estimated IntraMAT
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content of the quadriceps femoris (vastus lateralis [VL]) and hamstrings (long head of biceps femoris [BF]) between young and older adults using MRI and ultrasonography. We hypothesized that muscle volume and IntraMAT content in VL and BF would differ between young and older adults, due to differences in functional roles between QF and HM in daily physical activities.
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Journal Pre-proof 2. Materials and methods 2.1. Participants Fifteen physically active young individuals (8 men, 7 women) and 15 older individuals (7 men, 8 women) participated in this study. All subjects were living independently. The clinical histories of older adults were assessed using questionnaires. Older adults with a history of heart disease (myocardial infarction, angina pectoris, cardiac insufficiency), cerebrovascular disease (cerebral infarction, hemorrhage), extreme hypertension (systolic blood pressure ≥180 mmHg; diastolic blood pressure ≥110
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mmHg), or neuromuscular disorders were excluded. Moreover, none of the participants had any history of
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limb surgery. Young and older participants were recruited by university and local sports clubs designed
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specifically for older adults. The older adults had been participating once a week in local sports clubs designed for older individuals. All young and older individuals provided written informed consent prior to
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enrolment. This study was approved by the Ethics Committee of the Graduate School of Medicine Nagoya
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2.2. Magnetic resonance imaging
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University, and all protocols were in accordance with the guidelines in the Declaration of Helsinki.
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All participants refrained from participating in intense sport for 2 days before MRI. MRI was performed to acquire muscle volume using a 3.0 T MAGNETOM Verio (Siemens Healthcare GmbH, Eschborn, Germany) with a whole-body system to acquire muscle volume, muscle cross-sectional area (mCSA), and fat cross-sectional area (FCSA). We obtained a T1-weighted, spin-echo, axial-plane image (repetition time = 604 ms; echo time = 11 ms; matrix = 256 × 256; field of view = 256 mm; slice thickness = 10 mm; inter-slice gap = 0 mm) of the right thigh of participants in the morning. Participants were imaged in a supine position with pillows placed under the buttocks and leg to minimize tissue compression in the thigh. 2.2.1. Muscle volume, mCSA and fat cross-sectional area Muscle volume is considered the gold standard for estimating muscle size in humans. Muscle volume as determined from MRI was thus estimated as an index of muscle size. Muscle volumes of the VL and BF were estimated using 48 axial images from the right thigh, with the results transferred to a personal 7
Journal Pre-proof computer (Lets Note; Panasonic, Osaka, Japan) to estimate anatomical mCSAs from ImageJ software (version 1.47; National Institute of Health, Bethesda, MD). Muscle volume was determined by multiplying the sum of the mCSA of each image using the sum of thickness (10 mm) and inter-slice gap (0 mm) for each section. mCSA and fat cross-sectional area (FCSA) were determined from one image at the mid-thigh between the greater trochanter and lateral condyle of the femur, starting at the greater trochanter. A representative MRI for a young adult is shown in Figure 1. To minimize differences in body size, muscle volumes or mCSA of the VL and BF were normalized by body weight (muscle volume/weight and
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mCSA/weight).
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2.3. Ultrasonography
Ultrasonography scanning and analysis were performed by a single investigator (MH). Our study was
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not performed using a blinded method; therefore, ultrasonographic images were allocated serial numbers to
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prevent individual identification and were subsequently analyzed. All ultrasonography images were analyzed using Image J software. All participants refrained from participating in intense sport for 2 days
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before ultrasonography. Ultrasonographic measurements were performed twice, with an interval of at least
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1 week between measurements to test the reproducibility of the ultrasound technique. B-mode ultrasound scanning (LOGIQ e; GE Healthcare, Boston, MA) was performed by a single investigator. System-setting parameters were as follows: frequency, 8.0 MHz; gain, 80 dB; and depth, 8 cm. Participants were measured in the prone position with the leg fully extended and relaxed. Ultrasonographic images of the VL (lateral) and BF (posterior) were obtained at the mid-thigh between the greater trochanter and lateral condyle of the femur. All scans were made in the transverse plane with a linear transducer. An amount of contact gel was used to minimize the pressure of the transducer on the skin. Five images were scanned for each muscle. All images were stored in the ultrasonographic device in DICOM format for future analysis. 2.3.1. Muscle thickness and lateral or posterior subcutaneous thickness Muscle and subcutaneous tissue thicknesses were measured with electronic calipers placed at the middle of the ultrasound image (Fig. 2A, B). Muscle thickness was measured between the superficial and ventral muscle fascia, and subcutaneous tissue thickness was measured between the uppermost part of the 8
Journal Pre-proof skin and the superficial fascia of the muscle at the lateral and posterior sites. Three images were scanned for each part of the thigh, and these images were averaged for future analysis. To minimize the difference in body size, muscle thicknesses of the VL and BF were normalized by thigh length (muscle thickness/thigh length). 2.3.2. Intramuscular fat measurement by echo intensity Using echo intensity, as one of the indices reflecting IntraMAT in humans, intramuscular fat content was measured ultrasonographically. This was because our previous study clarified that echo intensity
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allows easy estimation of IntraMAT content in thigh muscles such VL (Akima et al., 2016). A region of
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interest (ROI) was selected in each of VL and BF, including as much of the muscle as possible on images,
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and bone and surrounding fascia were excluded. The smoothing function was applied to decrease noise in the ROI. Mean echo intensity of the ROI was calculated (8-bit resolution, resulting in a number between 0
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and 255, where black = 0, white = 255) (Fig. 2A, B). Mean echo intensity within the ROI in five images
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was measured for each muscle. To minimize variations in echo intensity due to technical errors, images with highest and lowest values of echo intensity were excluded. The remaining echo intensity in three
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images was averaged for future analysis. The mean coefficient of variation of the first and second
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measurements was 9.4 ± 8.6% in the VL and 5.7 ± 4.8% in the BF (at system setting parameter gain 80 dB) (n = 30 each). Coefficients of variation for VL and BF (> 10%) were fair, compared with the mean coefficients of variation reported by Young et al. (rectus femoris [RF], 5.6%; BF, 5.0%) (Young et al., 2015) and Scholten et al. (RF, 7.3%) (Scholten et al., 2003). Our previous study (Akima et al., 2016) showed that echo intensity correlated significantly with IntraMAT content of the VL and BF on MRI (VL, r = 0.404, p < 0.05; BF, r = 0.493, p < 0.01), and correlated significantly with EMCL of VL and BF by 1H-MRS (VL, r = 0.485, p < 0.05; BF, r = 0.648, p < 0.01).
2.4. Physical activity levels and dietary habits Physical activity levels were matched between young and older adults. The physical activity level was estimated from the records of the three-dimensional ambulatory accelerometer (Lifecorder; Suzuken Co., 9
Journal Pre-proof Nagoya, Japan) for 10 days. Habitual dietary intake was estimated using a food frequency questionnaire (Perez Rodrigo et al., 2015). The questionnaire asked about the average intake and frequency of consumption of each food. Dietary assessment indicated the energy (kcal/body weight), carbohydrate (g/body weight), protein (g/body weight), and fat (g/body weight) intakes for the dietary habits. Physical activity and habitual dietary intake details in young and older adults are shown in our previous studies (Hioki et al., 2019).
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2.5. Z score calculation
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Muscle volume, muscle volume normalized to body weight (muscle volume/weight), and echo
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intensity were normalized using Z-scores with individual data expressed as the number of standard deviations (SDs) from the mean for the young adult, calculated as: χ−μ σ
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𝑍=
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where χ is the value for individual adults, and μ and σ are the mean and SD, respectively, of the
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2.6. Statistics
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corresponding young adults (Maden-Wilkinson et al., 2014).
Data are expressed as mean ± SD. All data were compared using a two-way analysis of variance (ANOVA) with aging and sex as the between-group effects. Differences in muscle volume and echo intensity between VL and BF were evaluated using two-way ANOVA with aging and muscles. When a significant interaction effect was obtained, Bonferroni significant difference post-hoc analysis was utilized to determine specific differences. As the standard in the young adult, the Z-score was set to ± 2 SD (95% confidence interval) for muscle volume, muscle volume/weight, and echo intensity. The relationship between VL and BF in muscle volume or echo intensity, and the relationship between muscle volume/weight and echo intensity were determined using Pearson’s correlations analysis. Statistical significance was defined as p < 0.05. All statistical analyses were performed using SPSS version 24.0 software (SPSS Inc., Chicago, IL).
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Parts of the data have been reported previously. Those parts focused on different topics (extramyocellular lipid [EMCL] or intramuscular fat content as determined from MRI (Akima et al., 2016; Akima et al., 2015; Yoshiko et al., 2017) and intramyocellular lipid [IMCL] by 1H-magnetic resonance spectroscopy [1H-MRS]) (Hioki et al., 2016; Hioki et al., 2019), in contrast with the present topic
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(IntraMAT content by ultrasound).
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Journal Pre-proof 3. Results 3.1. Participant characteristics The characteristics of the participants are provided in Table 1. Overall, men were higher and heavier than women and young adults were higher and heavier than older adults. FCSA was higher overall in women than in men and higher in young women than in older women, but did not differ between young men and older men. In the older group, four participants had type 2 diabetes. Among these four participants with type 2
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diabetes, one was medicated with an -glucosidase inhibitor and thiazolidinedione, one with a dipeptidyl
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peptidase inhibitor, and two with metformin.
3.2. Muscle profiles
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The characteristics of muscle profiles are provided in Table 1. Muscle volume/weight was lower in
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older adults than in young adults, and lower in overall women than in men for VL and BF. Echo intensity was higher in older adults than in young adults for VL and BF, but did not differ between men and women.
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Regarding inter-muscle difference of muscle profiles, muscle volume of BF was significantly lower
0.0001).
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and echo intensity of BF was significantly higher than VL in older and young adults, respectively (p <
3.3. Physical activity level and dietary habits Characteristics of physical activity level and dietary intake habits are provided in Table 2. Physical activity level was not significantly different between young and older adults, and was not different overall between men and women. Regarding habitual dietary intake, protein intake was significantly higher in older adults than in young adults, but energy, carbohydrate and fat intake did not differ significantly between young and older adults. Energy, carbohydrate, protein and fat were significantly higher overall in women than in men.
3.4. Z-score 12
Journal Pre-proof Table 3 and Figure 3 show the Z-score in muscle volume, muscle volume/weight, and echo intensity for VL and BF of the young and older adults. Mean Z-score of the muscle volume/weight in older adults was 2 SD below the mean Z-score in young adults for VL (Fig. 3C), and that of the mean Z-score of the echo intensity in older adults was 2 SD above the mean Z-score in young adults for BF (Fig. 3F) (p < 0.05 each). In contrast, such a significant difference was not observed for muscle volume in VL and BF (Fig. 3A, B), or muscle volume/weight in BF (Fig. 3D) and echo intensity in VL (Fig. 3E).
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3.5. Correlations between VL and BF in muscle volume and echo intensity
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Figure 4 shows correlations between VL and BF in muscle volume, echo intensity of the young and
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older adults. A significant correlation was seen between VL and BF in muscle volume (r = 0.86, p < 0.001) (Fig. 4A) and echo intensity (r = 0.70, p < 0.01) (Fig. 4C) in the young adults. A significant correlation was
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seen between VL and BF in muscle volume (r = 0.65, p < 0.01) (Fig. 4B), but no relationship between VL
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and BF in echo intensity was observed in older adults (Fig. 4D).
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3.6. Correlations between muscle volume/weight and echo intensity in VL and BF
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Figure 5 shows correlations between muscle volume/weight and echo intensity in VL and BF of the young and older adults. A relationship between muscle volume/weight and echo intensity in VL and BF was not observed in young adults (Fig. 5A, C) or older adults (Fig. 5B, D).
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Journal Pre-proof 4. Discussion Our results support the hypothesis that muscle volume and echo intensity-estimated IntraMAT content in VL and BF differ between young and older adults. Muscle volume/weight was relatively lower in older adults than in young adults for VL, and echo intensity was relatively higher in older adults than in young adults for BF. A significant relationship was found between VL and BF in muscle volume of the young as well as in that of older adults, and a significant relationship was found between VL and BF in echo intensity of young adults, but not that of older adults. These results suggest that muscle volume of QF is
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less in older adults than in young adults, whereas the IntraMAT content of HM is greater in older adults
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than in young adults, and IntraMAT content correlated between QF and HM muscles in young adults, but
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not in older adults.
According to several studies, mCSA was lower in older male adults than in young male adults for QF
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(-14%) (Nilwik et al., 2013), and muscle volume was lower in older men than in young male and female
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adults for QF (-26.5%) (Hogrel et al., 2015), so the difference in mCSA is smaller compared with muscle volume. Our results also indicated differences in muscle volume/weight (VL, -29.3%; BF, -13.5%),
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mCSA/weight (VL, -24.2%; BF, -5.6%), and muscle thickness/thigh length (VL, -6.4%; BF, -3.8%).
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Roman et al. (Roman et al., 1993) reported that muscle volume, rather than mCSA or muscle thickness, is the most accurate measure for estimating muscle size. Our study therefore accurately measured age-related changes in muscle mass. Moreover, we used Z-scores to clearly judge the difference between older and young adults, showing that Z-scores for muscle volume/weight in VL were lower in older adults than in young adults (2 SD below the young adult mean). The loss in muscle strength of the lower extremity is greater than that of the upper extremity, presumably due to decreasing use of the lower limbs compared with upper limb muscles in older adults, and suggesting the main cause as muscle atrophy with aging (Frontera et al., 1991). Although total physical activity levels were similar between young and older adults, vigorous intensity physical activity level was lower in older adults than in young adults (Hioki et al., 2019). Age-related reductions in muscle mass might thus differ between QF and its antagonist muscle group (i.e., HM). However, the mechanisms underlying sarcopenia (loss of muscle mass) involve endocrine abnormalities, neuro-degenerative diseases, inadequate nutrition malabsorption, cachexia, and disuse 14
Journal Pre-proof (Cruz-Jentoft et al., 2010), among others, and we thus speculate that not only physical inactivity, but also multiple other factors might interact. We found that echo intensity was higher in BF than in VL in older adults as well as young adults, and changes in echo intensity between young and older adults were similar in VL (35.2%) as well as BF (33.6%). These results indicate that IntraMAT accumulation might be greater than the reduction in muscle volume with aging. Moreover, the Z-score of echo intensity in BF was higher in older adults than in young adults, and echo intensity was higher in BF than in VL among older adults in this study. Older individuals
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with increased IntraMAT in the lower limb muscles are known to show increased levels of muscle
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weakness, and decreased mobility limitation (Goodpaster et al., 2001; Visser et al., 2005; Visser et al.,
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2002). Although studies have focused on age-related changes in QF components, such age-related changes in muscle components might influence QF as well as HM functions in older adults. One effective approach
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to rehabilitation could thus be to decrease IntraMAT for thigh muscles (particularly, HM) in older adults.
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We found a significant relationship between echo intensity of VL and BF in young adults. Our results agreed with those reported by Young et al. (Young et al., 2016). Such evidence indicates a significant
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correlation between RF and BF for echo intensity-estimated IntraMAT content in adults (age range, 19-68
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years), suggesting that the characteristic IntraMAT content is similar in all muscles (Young et al., 2016). However, no such correlation was observed for older adults in the present study. Our findings suggest that IntraMAT accumulation in the leg cannot be characterized from a single muscle, especially when determining age-related changes in muscle components in older adults. Our results thus suggest that IntraMAT accumulation with aging is independent of muscle. Previous studies have reported that muscle attenuation correlated inversely with increased IntraMAT content (as measured using CT) in the thigh and calf muscles among young and older adults, subjects with type 2 diabetes (Goodpaster et al., 2000) and obesity (Tuttle et al., 2012). These results indicate that IntraMAT might infiltrate atrophied muscle. Furthermore, an animal study indicated that fat accumulation and fibrosis might lead to muscle atrophy (loss of muscle content) (Uezumi et al., 2011). However, our results indicated that no relationship existed between muscle volume and echo intensity in the muscles of both young and older adults. According to our previous study (Akima et al., 2015), IntraMAT content 15
Journal Pre-proof correlated with mCSA in some, but not all, muscle groups for both young and older groups (QF, HM, and adductors). These results suggest that atrophied muscle (lower muscle mass) in individuals seems essential for IntraMAT accumulation. Furthermore, Manini et al. (Manini et al., 2007) reported that as a result of 30 days of unilateral limb unloading, young healthy adults experienced a 15-20% increase in intermuscular adipose tissue (IMAT) of both the calf and thigh muscles, and this increase in IMAT exceeded the loss of lean tissue. These results indicate that IMAT might not just merely fill the space of lost muscle tissue. Age-related changes in muscle mass and IMAT or IntraMAT accumulation might not be tightly linked.
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Thus, such correlations might not be observed in older and young adults.
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This study has some limitations that need to be considered when interpreting the results. Our findings
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(estimated IntraMAT content by echo intensity) agree with a previous study that used MRI and 1H-MRS to estimate IntraMAT content. According to previous studies (Akima et al., 1997; Narici et al., 1989) using
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MRI, the change in the individual muscles of the lower thigh differs along the longitudinal axis of the thigh
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after physical inactivity or resistance exercise. These previous studies suggest that a single site and single muscle measurement for determining muscle size may lead to inaccurate estimates where changes in
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muscle size occur on MRI as well as ultrasonography. Ultrasonography has been widely used to evaluate
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atrophic muscle and echo intensity estimated-IntraMAT content in both study and clinical settings. However, muscle mass or IntraMAT content is estimated from part of the muscle in a narrow range of ultrasonographic images. Quantity and quality of thigh muscle are important for carrying out activities of daily living, and careful measurements are needed to achieve accurate estimates, especially QF and HM. We estimated IntraMAT content from echo intensity obtained from ultrasonography. However, echo intensity-estimated IntraMAT contains not only intramuscular adipose tissue, but also lipomatosis and fibrosis. Lipomatosis and fibrosis are unable to be completely removed. When sound is transmitted through tissue, attenuation of the ultrasound beam occurs because of reflection, dispersion, and absorption of the soundwaves (Pillen et al., 2008). Echo intensity thus reduces with depth. Higher subcutaneous fat thickness shows reduced echo intensity as depth increases. Sarcopenia is defined as muscle size falling below some lower limit, often defined as -2 SD below the values for young adults. Cutoffs set at 2 SD below the mean of a healthy, young adult population were recommended by the European Working Group 16
Journal Pre-proof on Sarcopenia in Older People (Cruz-Jentoft et al., 2010; Cruz-Jentoft et al., 2019). Maden-Wilkinson et
al. (2014) also used cutoffs set at 2 SD to determine sarcopenia. Therefore, our study also used cutoffs set at 2 SD. However, our study did not perform any a priori calculation of sample size. Our findings are thus better suited to hypothesis generation than precise determination of etiology.
5. Conclusion We assessed muscle volume and echo intensity-estimated IntraMAT in the QF and HM with different
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functional roles in daily physical activities by MRI and ultrasonography. These results suggest that muscle
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volume of QF is less in older than in young adults, whereas the IntraMAT content of HM is greater in older
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adults than in young adults, and IntraMAT accumulation was related between QF and HM muscles in young, but not in older adults. Assessment of IntraMAT accumulation thus needs to consider not only
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aging, but also the specific muscle. For the examination of muscle components, ultrasonography is easy
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and less expensive compared with MRI, CT, and DXA. Echo intensity-estimated IntraMAT could be helpful for rehabilitation professionals for evaluating aging muscle in rehabilitation and clinical settings.
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The degree to which these results can be generalized as a definition of sarcopenia (decrease in muscle size
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and increase in IntraMAT) is unclear, but warrants examination.
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Journal Pre-proof Declarations of interest
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The authors declare that they have no conflicts of interest.
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Journal Pre-proof Figure captions Fig. 1 Representative T1-weighted MRIs from a 21-year-old man. Dotted line indicates mCSA (A) and FCSA (B) at the mid-thigh. AM, adductor magnus; BF, long head of biceps femoris; BFs, short head of biceps femoris; Gr, gracilis; RF, rectus femoris; Sar, sartorius; SM, semimembranosus; ST, semitendinosus; VI, vastus intermedius; VM, vastus medialis; VL, vastus lateralis
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Fig. 2
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Representative ultrasonography images and MRIs demonstrate the same muscle site. Example of
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ultrasonographic scans of vastus lateralis (A) and long head of biceps femoris (B). These figures show an ultrasonographic image (left), a graphic representation of the scan (middle), and an MRI (above right).
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Dotted line in the middle panel indicates the region of interest (ROI) for echo intensity, and muscle and
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subcutaneous tissue thicknesses are indicated by dotted arrows. The bottom right panel indicates the ROI with gray-scale histograms. Ultrasonography was performed with the subject in the prone position, and
Fig. 3
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MRI was performed with the subject in the supine position
Comparison of muscle profile z-scores in young and older adults. Mean values for young adults (0, solid line) and ± 2 SD (dotted lines) are shown. BF, long head of biceps femoris; VL, vastus lateralis
Fig. 4 Pearson correlation coefficients for correlations between VL and BF in muscle volume normalized to body weight, echo intensity in the young (A and C) and older adults (B and D). a.u., arbitrary units; BF, long head of biceps femoris; VL, vastus lateralis
Fig. 5 Pearson correlation coefficients for correlations between muscle volume normalized to body weight and 22
Journal Pre-proof echo intensity from VL and BF in young (A and C) and older adults (B and D). a.u., arbitrary units; BF,
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long head of biceps femoris; VL, vastus lateralis
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Journal Pre-proof Author Statement
Maya Hioki: Methodology, Validation, Investigation, Data Curation, Writing - Original Draft, Formal analysis Nana Kanehira: Validation, Investigation, Data Curation Teruhiko Koike: Visualization, Writing - Review & Editing Akira Saito: Formal analysis, Investigation, Writing - Original Draft
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Kiyoshi Shimaoka: Resources
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Hisataka Sakakibara: Writing - Review & Editing
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Yoshiharu Oshida: Funding acquisition, Project administration
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Hiroshi Akima: Funding acquisition, Supervision, Conceptualization
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Journal Pre-proof Table 1 Participant characteristics young Men
older women
Men
women
% differ
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No. of participants 8 7 7 8 Physical characteristics Age (year) 21.0 ± 0.0 21.0 ± 0.0 71.1 ± 4.8 70.4 ± 2.9 Height (cm) 176.0 ± 6.5 157.3 ± 3.5 163.0 ± 2.7 152.1 ± 3.5 Weight (kg) 67.8 ± 8.0 55.9 ± 10.6 61.4 ± 4.5 50.9 ± 6.6 Thigh length (cm) 38.7 ± 1.3 33.8 ± 1.2 35.2 ± 1.3 32.2 ± 0.8 2 BMI (kg/m ) 21.9 ± 1.8 22.5 ± 3.5 23.1 ± 1.0 22.0 ± 2.7 2 FCSA (cm ) 40.0 ± 15.7 85.1 ± 23.5 35.5 ± 8.7 55.5 ± 13.7 Lateral subcutaneous thickness 0.4 ± 0.2 1.3 ± 0.4 0.5 ± 0.2 0.8 ± 0.3 (cm) Posterior subcutaneous 0.6 ± 0.3 1.4 ± 0.3 0.6 ± 0.2 0.7 ± 0.2 thickness (cm) Muscle profiles VL 3 Muscle volume (cm ) 535.5 ± 49.1 366.9 ± 60.3 369.4 ± 35.0 223.3 ± 37.1 -36.2 2 mCSA (cm ) 23.1 ± 2.2 18.7 ± 3.1 18.3 ± 1.8 11.1 ± 1.5 -31.1 Muscle thickness (cm) 1.9 ± 0.4 1.8 ± 0.3 1.7 ± 0.3 1.5 ± 0.4 -13.6 Muscle volume/weight 7.9 ± 0.6 6.6 ± 0.5 6.0 ± 0.7 4.4 ± 0.7 -29.3 mCSA/weight 0.34 ± 0.04 0.34 ± 0.04 0.30 ± 0.03 0.22 ± 0.04 -24.2 Muscle thickness/thigh length 0.05 ± 0.01 0.05 ± 0.01 0.05 ± 0.01 0.05 ± 0.01 -6.4 Echo intensity (a.u.) 54.5 ± 13.1 49.1 ± 5.8 69.8 ± 8.9 70.8 ± 9.6 +35.2 BF 3 Muscle volume (cm ) 176.2 ± 22.2 117.7 ± 27.3 128.9 ± 17.2 102.8 ± 17.7 -22.8 2 mCSA (cm ) 10.6 ± 1.3 8.8 ± 2.5 8.9 ± 1.1 7.8 ± 1.1 -15.4 Muscle thickness (cm) 2.1 ± 0.2 2.0 ± 0.3 2.0 ± 0.2 1.7 ± 0.3 -10.8 Muscle volume/weight 2.6 ± 0.3 2.1 ± 0.3 2.1 ± 0.3 2.0 ± 0.2 -13.5 mCSA/weight 0.16 ± 0.02 0.16 ± 0.03 0.14 ± 0.02 0.15 ± 0.02 -5.6 Muscle thickness/thigh length 0.05 ± 0.01 0.06 ± 0.01 0.06 ± 0.00 0.05 ± 0.01 -3.8 Echo intensity (a.u.) 65.0 ± 14.8 61.9 ± 2.2 82.7 ± 5.3 86.9 ± 8.5 +33.6 Value are means ± SD. a.u., arbitrary units; BF, long head of biceps femoris; BMI, body mass index; FCSA, fat cross-sectional area; mCSA, muscle cross-sectional area; VL, vastus lateralis. Data for older adults are expressed as a percentage of the difference value for young adults. All participants were the same as those previously reported by Akima et al. (2015, 2016), Hioki et al. (2016, 2019) and Yoshiko et al. (2017)
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Age effect
0.000 0.054 0.000 0.704 0.008 0.025 0.000
0.000 0.000 0.074 0.000 0.000 0.404 0.000 0.001 0.022 0.015 0.009 0.282 0.343 0.000
Journal Pre-proof Table 2 Physical activity and habitual dietary characteristics young Men women No. of participants Physical activity levels (kcal/day)
8 304.8 ± 90.2
older
7 223.2 105.5
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men
women
Age effect
7 203.8 ± 62.6
8 235.2 ± 88.2
0.179
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Habitual dietary intake Energy (kcal/body weight) 26.0 ± 6.5 32.4 ± 12.1 30.3 ± 4.4 35.3 ± 4.7 Carbohydrate (g/body weight) 3.5 ± 0.8 4.3 ± 1.5 4.0 ± 0.6 4.7 ± 0.8 Protein (g/body weight) 0.8 ± 0.3 1.1 ± 0.4 1.1 ± 0.3 1.4 ± 0.2 Fat (g/ body weight) 0.8 ± 0.3 1.1 ± 0.4 0.9 ± 0.3 1.2 ± 0.3 Value are means ± SD. All participants were the same as those previously reported by Akima et al. (2015, 2016), Hioki et al. (2016, 2019) and Yoshiko et al. (2017)
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0.190 0.222 0.010 0.717
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Table 3 Z scores of muscle component in young and older adults Young Older (n = 15) (n = 15) Muscle volume/weight VL 0±1 -2.41 ± 1.22* BF 0±1 -0.79 ± 0.62 Muscle volume VL 0±1 -1.63 ± 0.82 BF 0±1 -0.88 ± 0.56 Echo intensity VL 0±1 1.77 ± 0.86 BF 0±1 2.00 ± 0.68* * , p< 0.05 (significant ±2 SD); mean ± SD. BF, long head of biceps femoris; VL, vastus lateralis
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Journal Pre-proof Highlights
・ Muscle volume of quadriceps femoris is less in older than in young adults. ・ Intramuscular adipose tissue content of hamstrings is greater in older adults than in young adults. ・ Intramuscular adipose tissue accumulation was related between quadriceps femoris and hamstrings
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muscles in young, but not in older adults.
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Figure 1
Figure 2
Figure 3
Figure 4
Figure 5